LangGrant

Business leaders

Turn reports into ongoing decision intelligence

Start with work you already trust. Ask follow-up questions, refine the reasoning with human expertise, and reuse it for the next analysis.

AI developers

Automated database context MCP server for your AI stack

Give your AI apps existing schemas, SQL, reports, semantics, and other database work as relevant context—automatically chunked and kept current.

Tech leaders

Bring proven enterprise work to AI models

Use existing SQL, reports, policies, semantics, and human expertise instead of asking models to rediscover what your organization already knows.

Governed AI analytics. Human judgment. Reusable decision intelligence.

Use natural language database queries to ask business questions across enterprise data. Review the sources, assumptions and reasoning behind each answer.

Reasoning Plan / Margin analysis

Why is gross margin down?

SalesDW / SnowflakeERP_GL / OracleInventory / Postgres

Reasoning Plan

1. Apply approved definition of net revenue
2. Join sales and cost data
3. Compare with previous quarter
4. Break margin change down by driver

Human review✓ Approved

Answer
Deep discounts drove the margin decline.

Explain and defend every result

Show management, teams and stakeholders the data sources, definitions, joins, filters, calculations and assumptions behind the answer.

Review before you rely on it

Correct, annotate, collaborate, approve and version reasoning to reduce exposure to wrong answers, hallucinations and black-box reports.

Build on reusable AI reasoning

Reuse approved Reasoning Plans for recurring reports, follow-ups, future periods, other users and other models.

Ask → Reasoning Plan → Review → Approve → Reuse → Follow up

Your experts review the reasoning once. Your organization and AI can build on it repeatedly.

Database context for autonomous agents and AI apps

LangGrant supplies autonomous AI agents and applications with compact, current and relevant database context across large schemas, multiple databases and high request volumes.

Intelligent selection and chunking avoids dumping an entire schema into the prompt. LangGrant detects schema changes automatically, caches context and keeps it current for the next request.

Large schemas and high volumeMultiple databasesSchema change detectionContext cachingSQL, diffs and upgrade scriptsAnalytics and app development

An AI interoperability platform connecting models, agents and applications to the database context they need.

AI app / Agent / MCP client

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LangGrant Database Context

Selects relevant contextChunks large schemasResolves relationshipsDetects schema changesSupports multiple databasesFits model context windows

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SnowflakeOracleSQL ServerPostgresBigQueryand more

AI for enterprise data, grounded in knowledge you already trust.

Bring AI analytics to SQL Server, Snowflake, Oracle and other enterprise databases. Give models proven SQL, stored procedures, application code, data pipelines and documentation as context for new analysis. Carry forward established definitions and business semantics, building on years of tested engineering instead of asking AI to rediscover them.

Existing enterprise knowledge

Stored proceduresSQLApplication codeData pipelinesDocumentationApproved semantics

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LangGrant

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New work, grounded in what you know

AI applicationsReasoning PlansAnalyticsAutomation

Don’t make AI relearn what your organization already knows.

Put AI to work on your databases without throwing away human judgment or what your organization already knows.

See how LangGrant can fit your business users, AI stack and existing database environment.